• Korean Journal of Plant Resources
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• v.31 no.6
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• pp.641-651
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• 2018

Floral scents and metabolites from cut flowers of 14 peony cultivars (Paeonia lactiflora Pall.) were analyzed to discriminate different cultivars and to compare the Korean cultivar with the other cut peonies imported to Korea using electronic nose (E-nose) and Fourier transform infrared (FT-IR) spectroscopy combined with multivariate analysis, respectively. Principal component analysis (PCA) and discriminant function analysis (DFA) dendrogram of peony floral scents were not precisely same but there were 3 groups including same cultivars. PCA and partial least squares-discriminant analysis (PLS-DA) dendrograms of peony metabolites showed that different cut peony cultivars were clustered into two major groups including same cultivars. Fragrance pattern of Korean 'Taebaek' was classified to same group with 'Jubilee' on the PCA and DFA results and its metabolite pattern was clearly discriminated by the PCA and PLS-DA compared to the other cultivars. These results show that the 14 peony cut flowers could be discriminated corresponding to their chemical relationship and the metabolic profile of Korean 'Taebaek' has distinctive characteristics. Furthermore, we suggest that these results could be used as the preliminary data for breeding new cut peony cultivars and for improving the availability of Korean cut peony in cosmetic industry.

• Journal of Ginseng Research
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• v.37 no.3
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• pp.371-378
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• 2013

Serum and liver metabolites in rats fed red ginseng (RG) were analyzed by ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry. The mass data were analyzed by partial least squares-discriminant analysis (PLS-DA) to discriminate between control and RG groups and identify metabolites contributing to this discrimination. The RG group was clearly separated from the control group on PLS-DA scores plot for serum samples, but not liver samples. The major metabolites contributing to the discrimination included lipid metabolites (lysophosphatidylcholine, acyl-carnitine, and sphingosine), isoleucine, nicotinamide, and corticosterone in the serum; the blood levels of all but isoleucine were reduced by RG administration. Not all metabolites were positively correlated with the health benefits of RG. However, the blood levels of lysophosphatidylcholine, which stimulate various diseases, and long-chain acylcarnitines and corticosterone, which activate the stress response, were reduced by RG, suggesting long-term RG might relieve stress and prevent physiological and biological problems.

• Journal of Microbiology and Biotechnology
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• v.25 no.8
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• pp.1265-1274
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• 2015

Secondary metabolite-based chemotaxonomic classification of Streptomyces (8 species, 14 strains) was performed using ultraperformance liquid chromatography-quadrupole-time-offlight-mass spectrometry with multivariate statistical analysis. Most strains were generally well separated by grouping under each species. In particular, S. rimosus was discriminated from the remaining sevens pecies (S. coelicolor, S. griseus, S. indigoferus, S. peucetius, S. rubrolavendulae, S. scabiei, and S. virginiae) in partial least squares discriminant analysis, and oxytetracycline and rimocidin were identified as S. rimosus-specific metabolites. S. rimosus also showed high antibacterial activity against Xanthomonas oryzae pv. oryzae, the pathogen responsible for rice bacterial blight. This study demonstrated that metabolite-based chemotaxonomic classification is an effective tool for distinguishing Streptomyces spp. and for determining their species-specific metabolites.

• Journal of the Korean Wood Science and Technology
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• v.48 no.5
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• pp.591-607
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• 2020

This study was aimed to investigate the changes of chemical composition of the volatile organic compounds (VOCs) emitted from red pine needles in the process of needle abscission or senescence. The VOCs in intact, senescent, and litter red pine needle samples were analyzed by headspace-solid phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC/MS). And then, multivariate statistical interpretation of the processed data sets was conducted to investigate similarities and dissimilarities of the needle samples. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to investigate the dataset structure and discrimination between samples, respectively. From the data preview, the levels of major components of VOCs from needles were not significantly different between needle samples. By PCA investigation, the data reduction according to classification based on the chlorophyll a / chlorophyll b (Ca/Cb) ratio were found to be ideal for differentiating intact, senescent, and litter needles. The following OPLS-DA taking Ca/Cb ratio as y-variables showed that needle samples were well grouped on score plot and had the significant discriminant compounds, respectively. Several compounds had significantly correlated with Ca/Cb ratio in a bivariate correlation analysis. Notably, the litter needles had a higher content of oxidized compounds than the intact needles. In summary, we found that chemical compositions of VOCs between intact, senescent, and litter needles are different each other and several compounds reflect characteristic of needle.

• Korean Journal of Agricultural Science
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• v.47 no.3
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• pp.645-655
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• 2020

Bacteria are a very common cause of food poisoning. Moreover, bacteria form biofilms to protect themselves from harsh environments. Conventional detection methods for foodborne bacterial pathogens including the plate count method, enzyme-linked immunosorbent assays (ELISA), and polymerase chain reaction (PCR) assays require a lot of time and effort. Hyperspectral imaging has been used for food safety because of its non-destructive and real-time detection capability. This study assessed the feasibility of using hyperspectral imaging and machine learning techniques to detect biofilms formed by Escherichia coli. E. coli was cultured on a high-density polyethylene (HDPE) coupon, which is a main material of food processing facilities. Hyperspectral fluorescence images were acquired from 420 to 730 nm and analyzed by a single wavelength method and machine learning techniques to determine whether an E. coli culture was present. The prediction accuracy of a biofilm by the single wavelength method was 84.69%. The prediction accuracy by the machine learning techniques were 87.49, 91.16, 86.61, and 86.80% for decision tree (DT), k-nearest neighbor (k-NN), linear discriminant analysis (LDA), and partial least squares-discriminant analysis (PLS-DA), respectively. This result shows the possibility of using machine learning techniques, especially the k-NN model, to effectively detect bacterial pathogens and confirm food poisoning through hyperspectral images.

• Journal of Biosystems Engineering
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• v.38 no.4
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• pp.318-326
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• 2013

Purpose: We developed a viability evaluation method for cucumber (Cucumis sativus) seed using hyperspectral reflectance imaging. Methods: Reflectance spectra of cucumber seeds in the 400 to 1000 nm range were collected from hyperspectral reflectance images obtained using blue, green, and red LED illumination. A partial least squares-discriminant analysis (PLS-DA) was developed to predict viable and non-viable seeds. Various ranges of spectra induced by four types of LEDs (Blue, Green, Red, and RGB) were investigated to develop the classification models. Results: PLS-DA models for spectra in the 600 to 700 nm range showed 98.5% discrimination accuracy for both viable and non-viable seeds. Using images based on the PLS-DA model, the discrimination accuracy for viable and non-viable seeds was 100% and 99%, respectively Conclusions: Hyperspectral reflectance images made using LED light can be used to select high quality cucumber seeds.

• Mycobiology
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• v.42 no.4
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• pp.353-360
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• 2014

Makgeolli is a traditional Korean alcoholic beverage. The flavor of makgeolli is primarily determined by metabolic products such as free sugars, amino acids, organic acids, and aromatic compounds, which are produced during the fermentation of raw materials by molds and yeasts present in nuruk, a Korean fermentation starter. In this study, makgeolli was brewed using the wild yeast strain Saccharomyces cerevisiae Y98-5, and temporal changes in the metabolites during fermentation were analyzed by ultra-high-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry. The resultant data were analyzed by partial least squares-discriminant analysis (PLS-DA). Various metabolites, including amino acids, organic acids, sugar alcohols, small peptides, and nucleosides, were obviously altered by increasing the fermentation period. Changes in these metabolites allowed us to distinguish among makgeolli samples with different fermentation periods (1, 2, 3, 6, 7, and 8 days) on a PLS-DA score plot. In the makgeolli brewed in this study, the amounts of tyrosine ($463.13{\mu}g/mL$) and leucine ($362.77{\mu}g/mL$) were high. Therefore, our results indicate that monitoring the changes in metabolites during makgeolli fermentation might be important for brewing makgeolli with good nutritional quality.

• YAKHAK HOEJI
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• v.42 no.4
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• pp.359-363
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• 1998

Near infrared reflectance spectroscopy (NIRS) was applied for discrimination according to geographical origin (Korea, China) of herb drugs. Herbal medicine has an important role in clinical therapy in Asian countries such as Korea and China. The objective of this study is to provide a convenient and accurate method to determinate geographical origin (Korea, China) of herbal medicine for quality control whose quality is generally different according to geographical origin. A rapid, nondestructive and accurate discrimination was achieved by NIRS. Second derivative spectra of herb drugs were subjected to discriminant analysis. Herbal medicine drugs such as Cassia Semen, Ganoderma and Smilacis Rhizoma was discriminated accurately according to geographical origin using PLS regression method.

• Journal of Applied Biological Chemistry
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• v.65 no.4
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• pp.439-446
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• 2022

Soybean is a crop with high-quality of protein and oil, and it is one of the most widely used genetically modified (GM) crops in the world today. In South Korea, Kwangan is the most utilized variety as a parental line for GM soybean development. In this study, untargeted LC-MS metabolomic approaches were used to compare metabolite profiles of Kwangan and three other commercial varieties cultivated in Gunwi and Jeonju in 2020 year. Metabolomic studies revealed that the 4 soybean varieties were distinct based on the partial least squares-discriminant analysis (PLS-DA) score plots; 18 metabolites contributed to variety distinction, including phenylalanine, isoflavones, and fatty acids. All varieties were clearly differentiated by location on the PLS-DA score plot, indicating that the growing environment is also attributable to metabolite variability. In particular, isoflavones and linolenic acid levels in Kwangan were significantly lower and higher, respectively compared to those of the three varieties. It was discussed that it might need to include more diverse conventional varieties as comparators in regard to metabolic characteristics of Kwangan for the assessment of substantial equivalence biogenetically engineered soybeans in a Kwangan-variety background.

• Journal of the Korean Society for Nondestructive Testing
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• v.34 no.1
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• pp.31-37
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• 2014

The aim of this study was the non-destructive evaluation of bloody eggs using VIS/NIR spectroscopy. The bloody egg samples used to develop the sorting mode were produced by injecting chicken blood into the edges of egg yolks. Blood amounts of 0.1, 0.7, 0.04, and 0.01 mL were used for the bloody egg samples. The wavelength range for the VIS/NIR spectroscopy was 471 to 1154 nm, and the spectral resolution was 1.5nm. For the measurement system, the position of the light source was set to $30^{\circ}$, and the distance between the light source and samples was set to 100 mm. The minimum exposure time of the light source was set to 30 ms to ensure the fast sorting of bloody eggs and prevent heating damage of the egg samples. Partial least squares-discriminant analysis (PLS-DA) was used for the spectral data obtained from VIS/NIR spectroscopy. The classification accuracies of the sorting models developed with blood samples of 0.1, 0.07, 0.04, and 0.01 mL were 97.9%, 98.9%, 94.8%, and 86.45%, respectively. In this study, a novel nondestructive sorting technique was developed to detect bloody brown eggs using spectral data obtained from VIS/NIR spectroscopy.